System for controlling vehicle based on state of controller and system for controlling vehicle based on communication state

This application claims the benefit under 35 USC § 119(a) of Korean Patent Application Nos. 10-2022-0008946 and 10-2022-0013212, filed in the Korean Intellectual Property Office on Jan. 21, 2022, and Jan. 28, 2022, respectively, the entire disclosures of which are hereby incorporated by reference for all purposes.

The present disclosure relates to a system for controlling a vehicle based on a state of a controller and a system for controlling a vehicle based on a communication state.

In general, an autonomous driving system of a vehicle determines the driving condition of a vehicle, based on communication with controllers inside the vehicle, and communication with a roadside device or a surrounding vehicle around the vehicle, and automatically controls the vehicle driving based on the driving condition.

For example, a Departed Driver Rescue and Exit Maneuver (DDREM) system is a technology which allows the vehicle to stop safely when the driver suddenly falls into an inoperable state, such as drowsy driving or heart attack, and prevents accidents by automatically controlling the driving of the vehicle according to the driver condition.

The autonomous driving system transmits and receives a signal through Vehicle to X (V2X) communication with the roadside device or the surrounding vehicle and vehicle network communication with in-vehicle controllers (sensors) to control the driving condition of the vehicle. Accordingly, the communication state is an important factor in the autonomous driving.

This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

In one general aspect, here is provided a system for vehicle control. The system analyzes a state of each controller of multiple controllers inside a vehicle based on information collected from the controllers, learns the state of the each controller, based on a state analysis result obtained by analyzing the state of the each controller, and determines an abnormal state for at least one of the controllers, based on the state analysis result for the each controller and a learning result obtained by learning the state of the each controller. The system also includes a vehicle controller that manages vehicle control rights, based on the abnormal state for the at least one of the one or more controllers.

The processors may analyze at least one of an aging state, a fault state, response performance, a control amount, and a sensor state of each controller, based on the information collected from the controllers.

The processors may learn response performance of each controller, based on the state analysis result of the controller, select a control parameter for determining performance of the controller, based on the state analysis result of the controller, and learn a parameter value input from the controller, based on the selected control parameter.

When determining the abnormal state for the controllers, the processors may determine an abnormal state phase resulting from the abnormal state of the at least one of the controllers.

The vehicle controller may provide, to one of an autonomous driving controller and a manual driving control configured for operation by a driver, control rights over functions for supporting autonomous driving of the vehicle, based on the abnormal state phase resulting from the abnormal state of the at least one of the controllers.

The vehicle controller may provide, to the autonomous driving controller, all control rights over the functions for supporting the autonomous driving of the vehicle, when the determined abnormal state phase of the at least one of the one or more controllers is a first phase.

When the determined abnormal state phase of the at least one of the one or more controllers is a second phase, the vehicle controller may provide to the autonomous driving controller, control rights over some of the functions for supporting the autonomous driving of the vehicle, and query the driver, via the manual driving control, regarding control rights over a remaining portion of the functions for supporting the autonomous driving of the vehicle, and provide the control rights over the remaining portion of the functions to the autonomous driving controller or the manual driving control, depending on selection of the driver in response to the query.

The vehicle controller may provide, to the manual driving control, all of the control rights over the functions for supporting the autonomous driving of the vehicle, when the determined abnormal state phase of the controller is a third phase.

The vehicle controller may switch all of the control rights provided to the manual driving control to the autonomous driving controller, when manipulation of the manual driving control by the driver is not sensed for a specific time period.

In another general aspect, here is provided a system for vehicle control, based on a communication state. The system includes a first communication module configured communicate with controllers inside a vehicle, a second communication module configured to communicate with at least one of a roadside device and a surrounding vehicle around the vehicle, and a vehicle controller configured to analyze and learn a state of communication by the first communication module and the second communication module, determine an abnormal communication state of the vehicle, and determine a target to own a vehicle control right depending on the abnormal communication state of the vehicle.

The vehicle controller may include processors that analyze the state of the communication by the first communication module and the second communication module, learn the state of the communication by the first communication module and the second communication module, based on a result obtained by analyzing the state of the communication, and determine an abnormal communication state of the vehicle, based on the result, which is obtained by analyzing the state of the communication by the first communication module and the second communication module, and a result obtained by learning the state of the communication by the first communication module and the second communication module.

The processors may analyze consistency of a communication speed, a communication connection state, and communication data, based on the communication data between the first communication module and the controllers, analyze consistency and suitability of the communication speed, the communication connection state, and the communication data, based on vehicle to infrastructure (V2I) communication data between the second communication module and the roadside device, and analyze consistency and suitability of the communication speed, the communication connection state, and the communication data, based on vehicle to vehicle (V2V) communication data between the second communication module and the surrounding vehicle.

The processors may learn the communication speed and the communication state for each region, each terrain, and each attribute of communication data, with respect to the first communication module, the second communication module, and the controllers.

The processors may determine an abnormal communication state of at least one of the first communication module and the controllers, based on consistency of a communication speed, a communication connection state, and communication data between the first communication module and the controller, and determine an abnormal communication state of the second communication module, based on consistency and suitability of a communication speed, a communication connection state, and communication data among the second communication module, the roadside device, and the surrounding vehicle.

The processors may determine a phase of an abnormal communication state among at least one of the first communication module, the second communication module, and the controllers, when the abnormal communication state is determined.

The vehicle controller may determine, to an autonomous driving controller or a manual driving control configured for operation by a driver, a target to own one or more control rights over functions for supporting autonomous driving of the vehicle, based on the phase of the abnormal communication state.

The vehicle controller may determine, to the autonomous driving controller, a target to own all of the one or more control rights over the functions for supporting the autonomous driving of the vehicle, when the abnormal communication state is in a first phase.

The vehicle controller may determine, to the autonomous driving controller, the target to own some of the one or more control rights over the functions for supporting the autonomous driving of the vehicle, provide at least one of querying, via the manual driving control, the driver for the control right over the functions for supporting the autonomous driving of the vehicle, and determine a target to own the control right, depending on selection of the driver for the query, when the determined abnormal state phase of the controller is a second phase.

The vehicle controller may determine, to the manual driving control, a target to own the all of the one or more control rights over the functions for supporting the autonomous driving of the vehicle, when the abnormal communication state is in a third phase.

The vehicle controller may switch a target to own the control rights provided to the manual driving control to the autonomous driving controller, when manipulation of the manual driving control by the driver is not sensed for a specific time period.

Throughout the drawings and the detailed description, unless otherwise described or provided, the same drawing reference numerals will be understood to refer to the same elements, features, and structures. The drawings may not be to scale, and the relative size, proportions, and depiction of elements in the drawings may be exaggerated for clarity, illustration, and convenience.

The following detailed description is provided to assist the reader in gaining a comprehensive understanding of the methods, apparatuses, and/or systems described herein. However, various changes, modifications, and equivalents of the methods, apparatuses, and/or systems described herein will be apparent after an understanding of the disclosure of this application. For example, the sequences of operations described herein are merely examples, and are not limited to those set forth herein, but may be changed as will be apparent after an understanding of the disclosure of this application, with the exception of operations necessarily occurring in a certain order.

The features described herein may be embodied in different forms and are not to be construed as being limited to the examples described herein. Rather, the examples described herein have been provided merely to illustrate some of the many possible ways of implementing the methods, apparatuses, and/or systems described herein that will be apparent after an understanding of the disclosure of this application.

Advantages and features of the present disclosure and methods of achieving the advantages and features will be clear with reference to embodiments described in detail below together with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed herein but will be implemented in various forms. The embodiments of the present disclosure are provided so that the present disclosure is adequately disclosed, and a person with ordinary skill in the art can fully understand the scope of the present disclosure. Meanwhile, the terms used in the present specification are for explaining the embodiments, not for limiting the present disclosure.

Terms, such as first, second, A, B, (a), (b) or the like, may be used herein to describe components. Each of these terminologies is not used to define an essence, order or sequence of a corresponding component but used merely to distinguish the corresponding component from other component(s). For example, a first component may be referred to as a second component, and similarly the second component may also be referred to as the first component.

Throughout the specification, when a component is described as being “connected to,” or “coupled to” another component, it may be directly “connected to,” or “coupled to” the other component, or there may be one or more other components intervening therebetween. In contrast, when an element is described as being “directly connected to,” or “directly coupled to” another element, there can be no other elements intervening therebetween.

The singular forms “a,” “an”, and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises/comprising” and/or “includes/including” when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.

is a view illustrating a configuration of a system for controlling a vehicle, based on the state of a controller according to an embodiment of the present disclosure.

Referring to, the system (hereinafter, a vehicle control system) for controlling a vehicle based on the state of the controller may include a communication device, an analyzing device, a learning device, a determining device, a control device(for example, a vehicle controller), and a storage device. The communication device, analyzing device, learning device, determining device, and control device may be implemented via one or more processors.

The communication devicemay include controllers (or in-vehicle controllers)inside a vehicle and a communication module to make vehicle network communication. The technology for the vehicle network communication may include Controller Area Network (CAN) communication, Controller Area Network Flexible Data-Rate (CANFD), local interconnect network (LIN) communication, Flex-Ray communication, and Ethernet communication.

The communication devicemay receive state information on each of the controllersfrom the controllersduring driving. In this case, the controllersmay include a controller to support an autonomous driving function. The controllersmay include a sensor such as a camera, a radar, and a Lidar, and may control the operation of the sensor or process information obtained by the sensor.

For example, the controllersmay include a driving controller, such as Engine Management System (EMS), Electronic Stability Control (ESC), Electronic Stability Program (ESP), and Vehicle Dynamic Control (VDC). In addition, the controllersmay include an Advanced Driver Assistance System (ADAS) controller, such as Lane Keeping Assist System (LKAS), Highway Driving Assist (HDA), Smart Cruise Control (SCC)/Adaptive Cruise Control (ACC), Autonomous Emergency Brake (AEB)/Front Collision Avoidance assist (FCA), Highway Driving Pilot (HDP), Lane departure warning (LDW), Driver Attention Warning (DAW), or Driver State Warning (DSW).

Meanwhile, the communication devicemay further include a communication module for performing communication with a roadside device (not illustrated; surrounding roadside device) and/or a surrounding vehicle (not illustrated) around the vehicle using a wireless Internet access scheme or a short-range communication scheme. The wireless Internet technology may include a wireless LAN (WLAN), a wireless broadband (Wibro), a Wi-Fi, World Interoperability for Microwave Access (Wimax). In addition, short-range communication technology may include Bluetooth, ZigBee, Ultra-Wideband (UWB), radio frequency identification (RFID), or infrared data association (IrDA).

When receiving the information of each controller through the communication device, the analyzing devicemay analyze the state of each controller and the state of the sensor included in each controller, based on the received information.

In this case, the information of each controller received through the communication devicemay include fault information of the sensors included in the controllers and calibration state information of sensor data, and may include information such as fault information of the controllers, response performance of each controller, a control volume of each controller, the timing to replace to replace each controller, and the frequency of use of each controller.

For example, the analyzing devicemay analyze whether the timing to replace each controller has elapsed or whether the frequency of use of each controller exceeds the reference value based on the information received from each controller. In addition, the analyzing devicemay analyze whether the failure information of the sensor is included among the information received from each controller, or whether the calibration state of the sensor data falls within a normal range. In addition, the analyzing devicemay analyze whether the fault information of each controller is included in the information received from each controller, and whether the response performance of the controller and/or a control amount falls within the reference range.

The analyzing devicemay provide a result (hereinafter, a controller state analysis result) obtained by analyzing the state of each controller to the learning deviceand the determining device.

The learning devicelearns the state of each controller based on the controller state analysis result from the analyzing device. For example, the learning devicemay learn response performance such as the response time/the reaction time, the speed, and the control amount of each controller.

In this case, the learning devicemay select a plurality of control parameters necessary for maintaining basic performance of each controller and learn the parameter value of each controller for the selected plurality of control parameters. In this case, the learning devicemay learn a reference range of a parameter value for maintaining basic performance of each controller, with respect to a plurality of control parameters previously selected.

In addition, the learning devicemay compare a previous state information, which is previously learned, of a controller with present state information, which is presently learned, of the controller to learn the change in state of the controllers.

When learning of the state of the controller is completed, the learning devicemay provide the learning result (hereinafter, a controller state learning result) to the determining device.

Accordingly, the determining devicemay determine an aging state and/or an abnormal state for each controller, based on the controller state analysis result received from the analyzing deviceand the controller state learning result received from the learning device.

For example, when the response performance of some or all of the controllersdoes not satisfy the reference value, the determining devicemay determine that the relevant controller is in the aging state.

In addition, the determining devicemay determine whether the input values of each controller for a plurality of control parameters selected by the learning devicefall within the reference range and determine the controller as being in the abnormal state, when the input value is out of the reference range.